Nicholas J. Schork, Ph.D. Scripps Green Hospital Grand ...HR 3.09 Wall Street Journal 12/31/08 Nicholas J. Schork, Ph.D. Scripps Green Hospital Grand Rounds Wednesday, Feb. 18, 2009

Nicholas J. Schork, Ph.D.Scripps Green Hospital Grand Rounds

Wednesday, Feb. 18, 2009

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Genetic Risk Assessment

Nicholas J. Schork, Ph.D.

Scripps Translational Science Institute/Scripps Genomic MedicineScripps Health and The Scripps Research Institute

• The Case for Genetic Risk Assessment and Pharmacogenetics

• Gene Mapping and Genome-Wide Association (GWA) Studies

• Disease Prediction for Common Chronic Disease Based on Genetic Markers

• Race and Genetic Predisposition to Disease and Drug Response

• Contemporary Pharmacogenetics and the ‘Personalized Medicine Initiative’

The Case for Genetic Risk Assessment/Pharmacogenetics

Mukherjee and Topol, Prog Card Dis 44:479-98, 2002

Lack ofLack of

TrialTrial DrugDrug PlaceboPlacebo TreatedTreated Benefit/100Benefit/100 benefit/100benefit/100

HOPEHOPE RamiprilRamipril 17.817.8 14.014.0 3.83.8 96.296.2

APTCAPTC AspirinAspirin 14.014.0 10.010.0 4.04.0 96.096.0

FTTFTT ThrombolyticsThrombolytics 11.511.5 9.69.6 1.91.9 98.198.1

4S4S SimvastatinSimvastatin 28.028.0 19.019.0 9.09.0 91.091.0

EPICEPIC AbciximabAbciximab 12.812.8 8.38.3 4.54.5 95.595.5

CURECURE ClopidogrelClopidogrel 11.511.5 9.39.3 2.22.2 97.897.8

Adverse Event Rates (%)


The Case for Genetic Risk Assessment/Pharmacogenetics The Use of Drugs as an “Insurance” Measure: Side Effects



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• How can one only enroll those at risk for the outcome of interest in a drug trial?


• How can one match drugs to individuals that are likely to benefit from them?

• Can traditional risk factors (e.g., high cholesterol, race, etc.) be used?

• Does current information on genetic predisposition help or confuse the issue?

• How does one identify genetic risk factors? Are these methods reliable?

• What does the current data reveal? What else needs to be done?

• Will genetic counseling be accepted for common, non-Mendelian chronic diseases?

The Human Genome Project: What Next?

A focus on variation in human genome sequence and its role in phenotypic expression:

• The International HapMap Project (http://www.hapmap.org)• The Cancer Genome Atlas (TCGA) (http://cancergenome.nih.gov/)

These projects raise questions about how genetic variations behave in the population, as well what they do (physiologically) within an individual

Private Effort: Celera, Craig Venter Public Effort: Eric Lander, Francis Collins

Chromosomes, Genes, Proteins, and Polymorphism

The human genome is made up of 3,000,000,000+ x 2 bits of information This information is itself made up of a sequence of 4 bases (A,C,T,G) The human genome is spread out over 23 pairs of chromosomes One chromosome of each pair is inherited from each parent ~20,000-30,000 “genes” encode information that controls protein formation ‘Expression’ of genes is controlled by ‘regulatory’ genomic elements ~12,000,000+ sites in the human genome are ‘polymorphic’ Inherited variation occurs in ‘germ’ cells ‘Somatic’ cells make up the body and replicate (evolve) throughout life Much variation is ‘neutral,’ but some influences phenotypic expression Determining which variations influence which phenotypes is a major problem

Watson & Crick Double Helix 23 Human Chromosome Pairs DNA Sequencing Trace

International Haplotype Map (‘HapMap’) Project (www.hapmap.org)

• Multimillion Dollar Effort

• Multinational Effort (Second Generation Human Genome Project)

• Goals: Identify as many genetic variations as possible and define ‘haplotype block structure’ of the genome based on ‘linkage disequilibrium’ patterns among those variation

• Linkage Disequilibrium: the phenomenon whereby genetic variations (‘alleles’) at two loci are correlated due to a lack of recombination or population genetic factors such as admixture

…ACTAGATCGATCAGTTAGCTA… (haplotype 1)…ACTAGATCGATCAGTTAGCTA……ACTAGATCGATCAGTTAGCTA…

…ACTTGATCGATCAGCTAGCTA… (haplotype 2)…ACTTGATCGATCAGCTAGCTA……ACTTGATCGATCAGCTAGCTA…

The International HapMap and Genetic Mapping Panels



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Efficient Genotyping Technologies and GWAS Initiatives

• Single SNP genotyping costs have dropped ~1000 fold in the last 5 years• Affymetrix, Illumina, Sequenom, outsourcing, etc. make large-scale studies feasible• Recent initiatives emphasize Genome Wide Association (GWA) Studies

Important Issue:

The associated variations explain only a small fraction of the disease burden in the population at large!

The Recognition of Genetic Variation as Fundamental toAll of Biology and Biomedical Science in Particular

Genetic Risk Assessment For Common Chronic Diseases

Does the genetic information improve predictions based on traditional risk factors?

Can one predict ‘response to drugs’ as a phenotypic endpoint reliably?



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Consumer Genomics and Genetic Risk Assessment

Heightened Sensitivities among the Science Community…

November 10, 2008

Growing Interest and Fascination among the Lay Public…

The Navigenics Health Compass Report



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What Do Surveys Suggest About Effects of Genetic Risk?

Cogent Research survey on attitudes toward health behavior changes and personalgenetic risk (http://www.pgxreporter.com/issues/6_33/features/148793-1.html):

“more than half of all individuals surveyed said they are ready to make healthcare choices based on genetic test results. Specifically, the approximately 55 percent of respondents, or around 550 individuals, said they would increase the frequency of check-ups after receiving results from genetic tests, while about 13 percent said they would be willing to undergo voluntary prophylactic surgery based on results of their genetic test.”

“For affective outcomes, the majority of the studies reported negative effects on [risk gene] carriers but these were short-lived… Overall, predispositional genetic testing has no significant impact on psychological outcomes, little effect on behavior, and did not change perceived risk.” (Heshka et al. 2008).

A recent review of 35 focused cohort studies investigating health behavior changes after genetic risk assessment for specific diseases found no consistent negative emotional responses (i.e., fear) to genetic testing, and concluded that:

A study should focus on the effect of the provision of genetic risk on health surveillance behaviors, personal health behaviors, and psychological health

The Scripps Genomic Health Initiative

STSI, Navigenics, Affymetrix, Microsoft collaboration

Goal: 10,000 participants (enrollment until March 1, 2009)

3,000 Scripps Employees, Family Members and Patients

Affymetrix, Microsoft Employees are eligible as well

Personal Electronic Health Record in Microsoft HealthVault

1.8 Million SNPs (Affymetrix 6.0); Navigenics Health Compass

Baseline and Serial Follow-up Assessment

Exercise [Godin Leisure‐Time Exercise Questionnaire]

Nutrition [The Food Screener]

Psychological profile [STAI; Impact of Events Scale]

Medical screening and new diagnoses [CHIS]

www.navigenics.com/scripps

The Scripps Genomic Health Initiative

Diseases of Increased Frequency Associated with Different Populations

ETHNIC GROUP GENETIC DISORDER TYPICAL FEATURES Africans G6PD deficiency Anemia Afrikaners Porphyria variegata Neurological issues and sun sensitivity American Indians Cleft lip or palate (or both) Facial defect Amish/Mennonites Ellis-Van Creveld syndrone Dwarfism and extra digits Ashkenazi Jews Torsion Dystonia Disabling muscular and movements Ashkenazi Jews Tay-Sachs disease Brain degeneration Chinese Adult lactase deficiency Milk intolerance Eskimos Congenital adrenal hyperplasia Genital abnormalities and adrenal tumorsFinns Diastrophic dysplasia Dwarfism French-Canadian Familial hypercholesterolemia Coronary heart disease Irish Neural-tube defects Brain or spinal defects (e.g. spina bifida) Italians Fucosidosis Mental retardation Japanese Fukuyama congenital muscular dystrophy Muscle disease Japanese and Korean Actalasia Severe oral ulcers Maori: Polyneasians Clubfoot Foot deformity Mediterraneans Thalassemia (beta chain) Anemia Norwegians Cholestasis-lympedema Liver problems Yugoslavs Schizophrenia Psychosis

Is ‘race’ or genetic ancestry a good surrogate for genetic risk factors?

Can one use race to predict drug response as a phenotype?

Race, Genetic Background, and Drug Prescriptions



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Ancestry Informative Markers (AIMs)

• Ancestry Informative Markers (AIMs) are genetic variations that are found in higher frequency in one population rather than another

• If many such markers are identified, then one can use them to determine if an individual is likely to have ancestry from a specific population

• Additionally, one can genotype an individual on sets of AIMs associated with different populations to estimate the fraction of that person’s ancestry that is associated with different populations

• In this way, one can estimate an individual’s ancestry, but also the degree to which they are admixed from different populations

• If this is done for all the individuals in a sample, one can assess the diversity of the genetic backgrounds of those individuals and use this information in an association study to potentially correct for variation in admixture and heterogeneity

Example Admixture Studies Using AIMs: African Americans and Costa Ricans

Chicago African Americans(Halder, Shriver, et al. unpublished)

Costa Ricans(Shriver, et al. unpublished)

African Americans have genomes ‘between’ West Africans and Europeans but vary in degree of admixture

Costa Ricans have genomes ‘between’ Native Americans and Europeans but vary in degree of admixture

E J Parra, R A Kittles & M D Shriver (2004). Implications of correlations between skin color and genetic ancestry for biomedical research. Nature Genetics 36, S54 - S60

This map, based on the work of the geographer R. Biasutti, depicts average pigmentation levels across the world. Higher numbers represent darker skin color. Source; D. O'Neil (Behavioral Sciences Department, Palomar College, San Marcos, California, USA; http://anthro.palomar.edu/vary/vary_1.htm).

Global map of skin pigmentation levels

Table 1 Relationship of melanin content and individual ancestry

Samplea Spearman's rho (95% c.i.)b P

Relationship of melanin index and ancestry

African Americans (W-AF) 0.440 (0.330 to 0.538) <0.001

African Caribbeans (W-AF) 0.375 (0.239 to 0.496) <0.001

Mexicans (I-AM) 0.212 (0.057 to 0.357) 0.008

Puerto Ricans (W-AF) 0.633 (0.457 to 0.761) <0.001

Relationship of skin reflectance and ancestry

Hispanics (I-AM) -0.259 (-0.141 to -0.369) <0.001

aAncestral proportion axes are indicated by the abbreviations W-AF (West African) and I-AM (Indigenous American). bNinety-five percent confidence intervals for the correlation estimates are shown in parentheses.

E J Parra, R A Kittles & M D Shriver (2004). Implications of correlations between skin color and genetic ancestry for biomedical research. Nature Genetics 36, S54 - S60

http://www.dnaancestryproject.com/



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December 30, 2008; A1

Summary Table of 3 Series

Study Endpoint Number of Patients

Increased Risk of CYP2C19*2

Simon (FAST-MI) Death/MI/Stroke 2208 358%

Mega (TRITON) Death/MI/Stroke 1477 309%

Collet (AFIJI) Death/MI/Revasc 259 369%

NEJM and Lancet, Dec 22/23, 2008

HR 3.09

Wall Street Journal 12/31/08



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Recent FDA Precedent:

Warfarin (Coumadin)Labeling

Recent FDA Precedent:

CarbamazepineLabeling

Example Genotype-based Sampling for a Clinical Trials Example Genotype-based Sampling for a Clinical Trials

Senator Obama’s “Personalized Medicine Act” and the“Genetic Information Nondiscrimination Act” (GINA)

Parting Shot…

Why limit genetic risks to diseases or drug response? Why not study genetic profiling for reactions to ‘xenobiotics’ of all sorts? All drugs? Environmental exposures? Nutrients? Health?

Documents

Nicholas J. Schork, Ph.D. Scripps Green Hospital Grand ...HR 3.09 Wall Street Journal 12/31/08 Nicholas J. Schork, Ph.D. Scripps Green Hospital Grand Rounds Wednesday, Feb. 18, 2009